Metabolic syndrome, characterized by clustering of multiple metabolic abnormalities including abdominal obesity, dyslipidemia, hyperinsulinemia, hyperglycemia, and hypertension, is one of the most important risk factor for cardiovascular disease and stroke. Genetics plays a significant role in determining the individual susceptibility to metabolic syndrome and the inter-individual variation in its associated phenotypes, though these genetic factors remain largely unknown. Our long-term goal is to identify the metabolic syndrome susceptibility genes and their functional variants. The goal of the current application is to study the underlying phenotypic structure of metabolic syndrome and to systematically search for genetic loci predisposing metabolic syndrome using the genome scan approach. Our specific aims are: (1) to screen about 10,000 sibling pairs aged 40 to 64 years in Anqing, Anhui China, on intermediate phenotypes of metabolic syndrome including body mass index, waist and hip circumference, serum lipid profiles (triglyceride, HDL-, LDL-, and total cholesterol), fasting serum glucose and insulin level, and blood pressure; (2) to study the underlying phenotypic structure of metabolic syndrome in the about 10,000 ascertained sibling pairs using factor analysis; (3) to select and genome scan 800 nuclear families from the pool of the ascertained sibling pairs using Weber screening set 10 markers. Each selected nuclear family contains a "proband" and >=3 other family members. The values of the three most significant factors for metabolic syndrome in our factor analysis (see specific aim 2) will be used to classify "proband" status for each subject. A "proband" is defined as having >=2 out of 3 factor values falling into the same side of the 10/90 percentile tails of the corresponding age- and sex-adjusted population distributions; (4) to test for linkage in the genome-scanned families on intermediate phenotypes and factors of metabolic syndrome using the Unified Haseman-Elston method. In addition to the univariate test, we will perform linkage analysis using a novel multivariate version of the Unified H-E method, which has recently been proposed and shown to be significantly more powerful than the univariate test for traits with common genetic determinants; (5) to perform expansion or replication linkage studies on loci identified in the genome scan in 300-400 additional families with >=1 proband with a denser set of markers.